“We’ve missed our projected revenue by 40%,” said the CEO of Huddle to his senior team. And the question on everyone’s minds was —
How could they have gotten their sales forecast so wrong?
The misstep in sales forecasting was even more catastrophic for the Huddle team because they had made a number of business decisions, plans, and commitments based on hitting those targets.
In other words, optimism trumped accuracy in this example. But it doesn’t have to be this way. It’s undoubtedly challenging to “predict” the future and then compress it down into a single number.
But if you look at forecasting as an ongoing process, rather than a one-and-done methodology, you’ll be able to unlock the secrets of sales forecasting to improve business performance.
What is Sales Forecasting?
Sales forecasting is the process of predicting future sales performance for a business based on historical data, market trends, and other relevant factors.
By analyzing past sales data, companies can identify patterns and trends that can help them estimate future demand. Sales forecasting is crucial for businesses of all sizes and industries, as it allows them to make informed decisions about resource allocation, budgeting, and staffing.
Accurate sales forecasting methods can help companies avoid over or underproduction, prevent stock outs or overstocks, and optimize their pricing strategies.
The success stories of H&M and Zara prove as much:
- By adopting a modern IT infrastructure, H&M brought average lead times down by 20%. They can restock quickly with only best-selling products at economical prices.
- Zara maintains an incredibly streamlined supply chain using centralized resource planning managed through cloud based software — the clothing retailer only commits to 15-25% in production. 50% of its clothes are designed and manufactured while they’re in selling season — so they’re able to capture and respond to a best-selling item before or while the trend is peaking.
When it comes to demand and sales forecasting, “luck” is not part of the equation. Instead, it comes to real-time operations monitoring and integration with merchandise financial plans.
Additionally, sales forecasting can help companies plan for future investments in marketing and advertising, and identify opportunities for growth. Ultimately, sales forecasting is a vital tool for any business looking to make data-driven decisions and achieve sustainable success in today's competitive marketplace.
Benefits of Accurate Sales Forecasting
In 2011, BlackBerry was the market leader in the smartphone industry, with a 50% share of the market. So what went wrong? The company failed to accurately forecast the demand for touchscreen smartphones — instead, they released the BlackBerry Torch, a device that failed to capture the market share of touchscreen devices.
And like a series of dominos, a decline in sales then ensued, leading to a company- and brand-wide struggle to compete with rivals such as Apple and Samsung. BlackBerry's failure to accurately forecast the demand for touchscreen smartphones led to a decline in the company's market share, profitability, and overall success.
Flip this story around, though, and the benefits of accurate sales forecasting becomes clear:
Resource allocation is all about maintaining a clear understanding of the demand for products or services. If a business knows the numbers of project sales — or level of demand — in advance, they can work backwards, planning and allocating resources effectively.
This includes resources such as marketing, sales, and manufacturing. With accurate sales forecasts, businesses can plan their marketing campaigns, sales efforts, and production schedules based on anticipated demand, helping to prevent overstocking or stock shortages.
Effective resource allocation means cost savings by reducing wastage of resources and preventing unnecessary expenditure. Eventually, this leads to more efficient operations, better customer service, and increased profitability.
Risk and opportunity identification
Sales forecasting helps businesses to identify potential risks such as overstocking or stock shortages, which can be mitigated by adjusting inventory levels, production schedules, and procurement processes.
In addition, accurate sales forecasting can help businesses to identify opportunities for growth and expansion.
For example, if sales forecasts show an increase in demand for a particular product or service, businesses can invest in additional marketing, sales, and manufacturing resources to take advantage of this opportunity.
By anticipating changes in the market and making adjustments to their sales strategies, businesses can stay ahead of the competition and maintain a competitive edge.
Accurate sales forecasting sets the stage for informed and data-driven decisions. With a clear understanding of anticipated demand, businesses can make decisions about hiring, expansion, and other key business decisions.
For example, if sales forecasts show a significant increase in demand for a particular product or service, businesses can plan to hire additional staff or invest in expanding their production capacity to meet that demand.
On the other hand, if sales forecasts show a decline in demand, businesses can adjust their operations and strategies accordingly, such as reducing inventory levels, adjusting marketing strategies, or focusing on new product development. This helps avoid costly mistakes and make the most opportunities for growth and expansion.
Types of Sales Forecasting
- Is a method of sales forecasting that relies on expert opinions, judgment, and subjective inputs to predict future sales.
- Is more subjective and less data-driven.
- Methods can include surveys, focus groups, market research, and expert opinions.
- Is used when there is little historical data available or when the business environment is rapidly changing and unpredictable.
- Can be useful in situations where a business needs to make decisions based on subjective factors, such as changes in consumer behavior or emerging market trends.
- Can provide valuable insights and help businesses make informed decisions about their operations and strategies.
- Is a method of sales forecasting that uses historical data and statistical models to predict future sales.
- Relies on numerical data such as sales figures, customer behavior, and other key performance indicators to create a forecast of future sales.
- Methods can include time series analysis, regression analysis, and machine learning algorithms.
- Is used when historical data is available, and the business environment is relatively stable and predictable.
- Can be useful in situations where businesses need to make decisions based on data-driven insights, such as setting sales targets, production schedules, and inventory levels.
- Can be more accurate than qualitative forecasting, but it may not take into account subjective factors such as changes in consumer behavior or emerging market trends.
Smart businesses choose to use a combination of qualitative and quantitative forecasting methods to create a more accurate and comprehensive forecast of future sales.
- Is a quantitative forecasting method used to identify and analyze patterns and trends in historical sales data.
- Involves examining past sales data to identify patterns or trends that can be used to make predictions about future sales.
- Entails looking for patterns in sales data over time, such as seasonal fluctuations, long-term growth or decline, or changes in consumer behavior.
- Can be used by businesses to create a forecast of future sales.
- Can be useful in identifying sales patterns and trends that may not be immediately apparent, such as slow but steady growth over time or cyclical fluctuations that occur over a longer time frame.
- Relies solely on historical data and may not take into account external factors that can impact future sales, such as changes in the market, new competitors, or changes in consumer behavior.
Users of Sales Forecasting
Sales managers / Sales operations managers
Sales leaders use sales forecasting to plan and manage sales operations effectively.
Sales forecasting provides them with a clear picture of anticipated demand for the company's products or services, allowing them to plan production schedules, manage inventory levels, and allocate resources effectively.
Here are some ways in which sales operations managers use sales forecasting:
- Planning production schedules: Sales forecasting helps sales operations managers plan production schedules based on anticipated demand. They can use the forecast to schedule production runs and manage inventory levels, ensuring that the company has enough stock on hand to meet customer demand.
- Managing inventory: Sales operations managers use sales forecasting to manage inventory levels effectively. With a clear understanding of anticipated demand, they can adjust inventory levels accordingly, ensuring that the company has the right amount of stock on hand at all times.
- Allocating resources: Sales forecasting helps sales operations managers allocate resources effectively. They can use the forecast to plan sales and marketing campaigns, hire additional staff, and allocate budgets based on anticipated demand.
- Setting sales targets: Sales forecasting helps sales operations managers set sales targets and track performance against those targets. They can use the forecast to set realistic targets for sales ops and monitor progress towards those targets.
- Identifying trends: Sales forecasting helps sales operations managers identify trends in customer behavior and market conditions. They can use the forecast to identify emerging trends and adjust sales strategies accordingly.
Revenue operations and sales teams rely on sales forecasting to get a clear picture of anticipated revenue for the company's products or services, allowing them to plan and manage revenue streams effectively. Here are some ways in which revenue operations teams use sales forecasting:
- Planning and managing budgets: Revenue operations teams use sales forecasting to plan and manage budgets effectively. They can use the forecast to allocate budgets based on anticipated revenue streams, ensuring that the company has enough resources to support its operations.
- Managing revenue streams: Sales forecasting helps revenue operations teams manage revenue streams effectively. With a clear understanding of anticipated revenue, they can adjust revenue streams accordingly, ensuring that the company has the right mix of revenue streams to achieve its goals.
- Tracking performance: Revenue operations teams use sales forecasting to track performance against revenue targets. They can use the forecast to set realistic revenue targets and monitor progress towards those targets, making adjustments as necessary to achieve their goals.
- Identifying trends: Sales forecasting helps revenue operations teams identify trends in customer behavior and market conditions. They can use the forecast to identify emerging trends and adjust revenue strategies accordingly.
- Optimizing pricing: Revenue operations teams use sales forecasting to optimize pricing strategies. They can use the forecast to set prices that are aligned with anticipated revenue streams, ensuring that the company is pricing its products or services appropriately.
Finance departments use sales forecasts to plan and manage the financial resources of the company. Sales forecasting provides them with a clear picture of anticipated revenue, which allows them to make informed decisions about budgets, cash flow, and financial planning.
Here are some ways in which finance departments use sales forecasts:
- Budgeting: Sales forecasting helps finance departments plan and manage budgets effectively. They can use the forecast to allocate budgets based on anticipated revenue streams, ensuring that the company has enough resources to support its operations.
- Cash flow management: Sales forecasting helps finance departments manage cash flow effectively. With a clear understanding of anticipated revenue, they can adjust cash flow accordingly, ensuring that the company has enough cash on hand to meet its financial obligations.
- Financial planning: Sales forecasting helps finance departments with financial planning. They can use the forecast to make informed decisions about investments, financing, and other financial activities.
- Performance tracking: Finance departments use sales forecasting to track performance against financial targets. They can use the forecast to set realistic revenue targets and monitor progress towards those targets, making adjustments as necessary to complete their goals.
- Risk management: Sales forecasting helps finance departments with risk management. They can use the forecast to identify potential risks and take appropriate measures to mitigate those risks.
Best Techniques for Sales Forecasting
To use historical data for accurate sales forecasting, businesses need to analyze their past sales data effectively.
To start, businesses need to gather and organize historical sales data, which can include product sales, revenue, and customer behavior. Once the data is collected, they can use various statistical models and tools to analyze the data, such as regression analysis and time-series analysis.
Analyzing data helps businesses to identify trends in sales volume, customer demographics, and market demand. This can help them understand how their sales have changed over time and what factors influenced those changes.
Based on the insights gained from historical sales data, businesses can develop more accurate and reliable sales forecasts. They can use these forecasts to make data-driven decisions about inventory management, pricing strategies, and other key business operations, ultimately improving their overall sales performance.
Collaboration across departments
When multiple departments work together, they can share data and insights that improve the accuracy of sales forecasts.
- Sales department can provide valuable information about customer behavior and preferences
- The marketing department can share insights on market trends and competition.
- The finance department can contribute by providing financial data, such as revenue and budget information.
When all of this data is shared and analyzed collectively, businesses can develop more accurate sales forecasts.
Collaborating across departments can also help businesses identify potential risks and opportunities, allowing them to adjust their strategies accordingly.
For example, if the marketing department identifies a new trend in customer behavior, the sales department can use that information to adjust their sales forecasts, ensuring that they are aligned with the latest market trends.
Staying up to date with industry trends
As the market changes and new trends emerge, businesses need to adjust their sales cycle accordingly. By keeping up with the latest industry news and trends, businesses can stay ahead of the competition and adjust their sales strategies to stay relevant.
For example, if a new product becomes popular in the market, businesses need to be aware of the trend and adjust their sales pipeline accordingly.
Tools for Sales Forecasting
Customer relationship management (CRM) systems track sales data and customer behavior, allowing businesses to analyze their sales history and identify trends.
Businesses can use this data to create forecasts that are based on historical data and customer behavior.
For example, a CRM system can be used to track customer interactions, such as phone calls, emails, and website visits. This data can be used to identify trends in customer behavior and preferences, such as which products are popular or which sales channels are most effective.
By analyzing this data, businesses can develop more accurate sales forecasts that take into account the latest market trends and customer behavior. CRM systems can also be used to identify potential risks and opportunities, such as changes in customer behavior or shifts in the market.
Data analytics tools
Data analytics tools analyze sales data in detail, identify trends, and make predictions based on past performance. Businesses armed with this information can take a more data-driven approach to sales forecasting, which can help to improve the accuracy of their forecasts.
For example, data analytics tools can be used to identify patterns in customer behavior, such as buying habits or preferred sales channels. These insights can then be used to create more accurate forecasts, which can help businesses to allocate resources more effectively and make better-informed decisions.
Forecasting tools help businesses automate the sales forecasting process, allowing them to save time and resources while still generating accurate forecasts.
Forecasting software considers various factors such as historical sales data, market trends, and customer behavior, to generate forecasts that are tailored to the specific needs of each business.
This helps businesses reduce the risk of human error and improve the accuracy of their forecasts, which can help them make better-informed decisions about resource allocation, marketing strategies, and other key business decisions.
The numbers that track the state of sales forecasting paint an interesting picture:
- 40% of companies use sales forecasting tools to predict future sales.
- 70% of sales forecasting is inaccurate due to lack of data
- Analysts spend up to 20 hours a week on sales forecasting
- Organizations that use sales forecasting experience an 8% increase in revenue
- 45% of sales reps use artificial intelligence for sales forecasting
What we can draw from this is that companies are using sales forecasting tools but aren’t necessarily targeting the right data (or receiving enough).
There is a turn towards AI and ML for predictive, real-time forecasting, but it isn’t (yet) a focused activity across the board. And organizations that do use some type of forecasting report an 8% rise in revenue — but is that from sales? And is 8% a realistic upper limit if 70% of sales forecasting is inaccurate to begin with?
As an activity, sales forecasting is only useful when it’s accurate. In other words, to realize these benefits, you’ll need to employ the best practices and proven approaches we’ve explored in this article. Successful sales forecasting works well only when and if you work it — consistently, and with all the moving parts in place.
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